Numerical Optimization: Understanding L-BFGS — aria42Numerical Optimization: Understanding L-BFGS Numerical optimization is at the core of much of machine learning. Once you’ve defined your model and have a dataset ready, estimating the parameters of your model typically boils down to minimizing some multivariate function $f(x)$, where the input $x$ is in some high-dimensional space and corresponds to model parameters. In other words, if you solve:
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